Ciao-Wps Automatic And Intelligent Orchestration Of Geospatial Web Services Using Semantic Web (Web 3.0) Technologies

Current geospatial datasets and web services are disparate, obscure and difficult to expose to the world. With the advent of geospatial processes utilizing temporal data and big data, along with datasets continually increasing in size, the problem of under-exposed datasets and web services is amplified. Current text search capabilities do not sufficiently expose web services and datasets for use in on-the-fly geospatial use cases. End users are required to know the exact location of these online resources, their format and what they do. For example, to locate an OGC (Open Geospatial Consortium - http://www.opengeospatial.org)-compliant WPS (Web Processing Service) that performs flood modelling, a Google Search for "Flood Modelling WPS" is insufficient to find relevant results. This paper proposes the integration of semantic web concepts and technologies into geospatial datasets and web services, making it possible to link these datasets and services via functionality, the inputs required and the outputs produced. To do so requires the extensive use of metadata to allow for a standardised form of description of their function. There are already ISO (International Organization for Standardization - www.iso.org) standards in place (ISO 19115-1: 2014) that specify the schema required for describing geographic information and services. The use of ontologies and AI (Artificial Intelligence) then allows for the intelligent determination of which web services and datasets to use, and in what order they are to be used to achieve the desired final output. This research aims to provide a method to automatically and intelligently chain together web services and datasets to assist in a geospatial analyst's productivity. A simple prototype termed CIAO-WPS (Chet's Intelligent, Automatically-Orchestrated Web Processing Services) is created as a proof of concept, using the Python programming language. The prototype seeks to reinforce ideas in regards to pathing and cost constraints, as well as explore overlooked designs.